Data Mining in Fault Injection

نویسندگان

  • András PATARICZA
  • Gergely PINTÉR
چکیده

This paper outlines a method and environment for reflecting the effects of faults in the behavioral software models providing a way for building abstract reusable fault models that are applicable even in early phases of the software development. The main focus is on the application of intelligent data processing methods for extracting important phenomena from the database of fault injection experiments.

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تاریخ انتشار 2003